Cortis, Keith and Freitas, Andre and Daudert, Tobias and Huerlimann, Manuela and Zarrouk, Manel and Handschuh, Siegfried and Davis, Brian (2017) SemEval-2017 Task 5: Fine-Grained Sentiment Analysis on Financial Microblogs and News. In: 11th International Workshop on Semantic Evaluations (SemEval-2017): Proceedings of the Workshop. Association for Computational Linguistics (ACL), Stroudsburg, PA, USA, pp. 519-535. ISBN 978-1-945626-55-5

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Abstract

This paper discusses the “Fine-Grained Sentiment Analysis on Financial Microblogs and News” task as part of SemEval-2017, specifically under the “Detecting sentiment, humour, and truth” theme. This task contains two tracks, where the first one concerns Microblog messages and the second one covers News Statements and Headlines. The main goal behind both tracks was to predict the sentiment score for each of the mentioned companies/stocks. The sentiment scores for each text instance adopted floating point values in the range of -1 (very negative/bearish) to 1 (very positive/bullish), with 0 designating neutral sentiment. This task attracted a total of 32 participants, with 25 participating in Track 1 and 29 in Track 2.

Item Type:	Book Section
Additional Information:	The 11th International Workshop on Semantic Evaluations(SemEval-2017)was held in Vancouver, Canada from 3 to 4 August, 2017
Keywords:	Fine-Grained Sentiment Analysis; Financial Microblog; News; Detecting sentiment, humour, and truth;
Academic Unit:	Faculty of Science and Engineering > Computer Science Faculty of Science and Engineering > Research Institutes > Hamilton Institute
Item ID:	11841
Identification Number:	https://doi.org/10.18653/v1/S17-2
Depositing User:	IR Editor
Date Deposited:	28 Nov 2019 10:18
Publisher:	Association for Computational Linguistics (ACL)
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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